A survey of intrusion detection techniques
Computers and Security
Testing and evaluating computer intrusion detection systems
Communications of the ACM
NEFCLASSmdash;a neuro-fuzzy approach for the classification of data
SAC '95 Proceedings of the 1995 ACM symposium on Applied computing
The 1999 DARPA off-line intrusion detection evaluation
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue on recent advances in intrusion detection systems
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Network Intrusion Detection: An Analyst's Handbook
Network Intrusion Detection: An Analyst's Handbook
Applying CMAC-Based On-Line Learning to Intrusion Detection
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5 - Volume 5
A Computer Host-Based User Anomaly Detection System Using the Self-Organizing Map
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5 - Volume 5
Proceedings of the 5th international conference on Recent advances in intrusion detection
RAID'02 Proceedings of the 5th international conference on Recent advances in intrusion detection
Training a neural-network based intrusion detector to recognize novel attacks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Review: The use of computational intelligence in intrusion detection systems: A review
Applied Soft Computing
Information Sciences: an International Journal
Detecting anomalous network traffic with combined fuzzy-based approaches
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part II
Network anomaly detection with bayesian self-organizing maps
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
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With the rapidly increasing impact of the Internet, the development of appropriate intrusion detection systems (IDS) gains more and more importance. This article presents a performance comparison of four neural and fuzzy paradigms (multilayer perceptrons, radial basis function networks, NEFCLASS systems, and classifying fuzzy-k-means) applied to misuse detection on the basis of TCP and IP header information. As an example, four different attacks (Nmap, Portsweep, Dict, Back) will be detected utilising evaluation data provided by the Defense Advanced Research Projects Agency (DARPA). The best overall classification results (99.42%) can be achieved with radial basis function networks, which model hyperspherical clusters in the feature space.